We now live in the digital age. If Facebook were a country, it would already be the third most populous in the world. Mobile phones are on track to outnumber the human race by the end of this year. We have never been so connected, and these digital interactions are creating trillions of terabytes of data, waiting to be leveraged by marketers.
The sheer amount of data and digital noise can be overwhelming; however, the benefits for brands and marketers of harnessing and understanding these massive data stores include the potential for increased customer acquisition, reduced overhead, and smarter, faster, more targeted decisions.
Today, demand side platforms (DSPs) have become among the most powerful tools in the marketing arsenal of the digital age. They employ sophisticated algorithms to determine where a marketer should place adverts in order to convert customers and garner the best return on investment. In the old days, when a marketer wanted to buy advertising—TV, print, radio, even online—they would have lunch with the seller, talk about the rate, and fax over an insertion order. DSP platforms have replaced that with a machine-to-machine trading protocol that automates and elevates media buys.
DSPs have been shown in various studies to increase return on marketing investment by 20-50%, increase media efficiency up to 40%, and save 25% in overhead costs through ad-buying automation. But the real benefit of DSPs is the by-product—data. Which types of individuals are responding to ads, in what city, and at what times of day or days of the week? These questions can be answered with ease if the data captured by the DSP can be stored and analysed.
When DSPs were first introduced, there was little consideration of the value of the data they produced. Often the information was discarded and the opportunity to use the data for future decisions was missed. However, as demand and understanding grew, the sector continued to evolve and the next incarnation included full marketing management platforms that were integrated with the DSP.
To my knowledge, DataXu was the first to catch on to the enormous value of the data and introduce a consolidated digital marketing management (DMM) platform—DX3. In simple terms, the introduction of the DMM combines the programmatic buying of a DSP with data management, attribution-aware buying, insights, and reporting.
With DX3, the process is fairly straightforward: marketers start by entering objectives, and then they put measurement tags on assets: website, mobile app, videos, and ads distributed through any channel. When those tags are in place, data starts to flow into DataXu’s learning system. Say you’re Standard Chartered, and you are trying to get consumers to use your credit cards. The DataXu system correlates the Standard Chartered ads a consumer has seen and the content they’ve consumed, as well as whether they ever visited a particular digital channel.
Did Standard Chartered show the customer ads? Yes, the customer did a Google search for credit card reviews and went to The Daily Telegraph site where he or she saw a banner ad. DataXu uses that information to correlate the consumer journey from awareness to preference to conversion. Every time an ad is served, DataXu says: “We served this particular creative message, to this browser, at this time of day, in this particular semantic context, knowing these particular things about the consumer.” DataXu continually learns from those parameters to understand which are most likely to result in a conversion event, in order to inform future buying decisions.
Over the space of a week or two, a distinctive pattern emerges: People exposed to ads on Sunday nights in London are more likely to sign up for a credit card on Tuesday during the work day. DX3 ranks these patterns such as: The variable most predictive of conversion was location, second was watching a particular video, and third was a history of visiting financial sites. This forms a data model.
Traditionally, marketers would conduct a panel and ask people for their attitudes about Standard Chartered. DataXu is using the ad as a platform for behavioral research—did people engage or not—and creating a model that predicts behavior based on evidence gleaned from the digital lifestyle.
In an evolutionary sense, the DMM is the missing link that brands and marketers had been asking for. Through the DMM platform, the constant influx of data, those billions and trillions of terabytes, can be transformed into insight for brands and provide the means to make intelligent decisions and improve on marketing initiatives—literally in an instant.